Add svm.py to machine_learning

Author: marcoslozina

machine_learning/svm.py

@@ -0,0 +1,32 @@
+from sklearn.model_selection import GridSearchCV
+import numpy as np
+import matplotlib.pyplot as plt
+from sklearn import datasets
+from sklearn.model_selection import train_test_split
+from sklearn.svm import SVC
+from sklearn.metrics import accuracy_score, classification_report, confusion_matrix
+from sklearn.datasets import load_breast_cancer
+data=load_breast_cancer()
+X,y=data.data,data.target
+
+X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.3,random_state=42)
+
+param_grid={
+    'C':[1, 10],
+    'kernel':['linear','rbf'],
+    'gamma':['scale']
+}
+
+svm=SVC(random_state=42)
+
+grid_search=GridSearchCV(svm, param_grid, cv=3, scoring='accuracy', n_jobs=-1, verbose=1)
+grid_search.fit(X_train,y_train)
+
+print("Best parameters:",grid_search.best_params_)
+print("Best cross validation score",grid_search.best_score_)
+
+best_svm=grid_search.best_estimator_
+y_pred=best_svm.predict(X_test)
+test_accuracy=accuracy_score(y_test,y_pred)
+print(f"Test accuracy:,{test_accuracy:.2f}")
+